THE KNEE SOCIETY VIRTUAL FELLOWSHIP. Robotics in Knee Arthroplasty Presented by: Jess H. Lonner, MD Rothman Institute Philadelphia, PA

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1 THE KNEE SOCIETY VIRTUAL FELLOWSHIP Robotics in Knee Arthroplasty Presented by: Jess H. Lonner, MD Rothman Institute Philadelphia, PA

2 DISCLOSURES Royalties Zimmer Biomet, Smith and Nephew Consultant Zimmer Biomet, Smith and Nephew Speaker s bureau Zimmer Biomet, Smith and Nephew Publishers: Saunders, Lippincott Williams Wilkins, Springer Shareholder: Blue Belt Technologies, CD Diagnostics

3 ROBOTS IN INDUSTRY Efficient Economical Exacting

4 Robotics industry today is where the PC industry was 30 years ago. ** Bill Gates, Scientific American 2007 BILL GATES **(Especially healthcare)

5 EXPERIENCE WITH ORTHOPAEDIC ROBOTS Initial skepticism Early adopters showed value Alignment Soft tissue balance Recovery Blood loss Safety (semi-autonomous) Increased utilization with pricing improvements Lonner JH. Operative Techniques in Orthopaedics 2015

6 STORY OF ROBOTICS IN KNEE ARTHROPLASTY Study in patterns that define technological progress and innovation, in general Newer companies/technologies Declining capital and maintenance costs Smaller space requirements Broadening access Increased utilization Expanding applications Lonner JH. Operative Techniques in Orthopaedics 2015

7 STAKEHOLDERS WILL INFLUENCE FURTHER GROWTH OF ROBOTICS

8 EXPANDING ROLE FOR ROBOTICS IN UKA 15% of UKA s in US (2013)

9 PATENTS AS A SURROGATE INDICATOR OF INNOVATION Dalton DM et al. J Arthroplasty 2016

10 ROBOTIC LANDSCAPE: PROJECTED PENETRATION UKA ~29% in five years ~37% in 10 years TKA ~10% in two years ~18% in five years ~23% in ten years Medical Device and Diagnostic Industry, March 5,

11 KEY DISTINCTION IN ORTHOPAEDIC ROBOTICS Autonomous- robot operates independently TCat (formerly Robodoc) ithink Surgical FDA approved for THA Not FDA approved for TKA Semi-autonomous- surgeon guided; haptic or speed/exposure constraint Mako (Stryker) FDA approved for THA, UKA, PFA, TKA Navio (Smith and Nephew) FDA approved for UKA, PFA, TKA OmniBot (Omni) FDA approved for TKA

12 COMPLICATIONS WITH AUTONOMOUS SYSTEMS Complications THA Soft tissue injuries, over-resection Severe abductor injuries/sciatic nerve injuries 18% revision due to instability (vs 4% control) Aborted cases TKA 8% soft tissue injury Honl et al JBJS 2003 Chun et al J Arthrop 2011

13 ADVANCEMENT OF SEMI-AUTONOMOUS ROBOTIC SYSTEMS Safety and avoidance of soft tissue complications has been key distinction

14 ROBOTICS FOR TKA? Unclear need for precise alignment Potential roles: Optimizing soft tissue balance? Bicruciate retaining TKA? Access, balance Facilitating efficiencies? Reducing instrument storage/sterilization needs/costs? Applicable for ASC s

15 ROBOTICS FOR UKA? 94% survivorship at yrs in hands of high volume surgeons

16 BUT > Age 65 < Age yr survivorship 77% 7-yr survivorship 74% Ong, Kurtz, Hansen, Lonner AAHKS 2014

17 WHAT IMPACTS THE RESULTS OF UKA? Pathology/Disease Patient selection Component design Polyethylene quality Surgeon experience/volume Accuracy of implantation Soft tissue balance

18 MALALIGNMENT PREDISPOSES TO FAILURE Coronal malalignment of tibial component >3 varus Mechanical limb varus >8 Posterior tibial slope >7 Collier /Engh et al. J Arthroplasty 2006; Hernigou JBJS 2004; Chatellard Orthop Traumatol Surg Res 2013

19 UKA MALALIGNMENT > IN MIS THAN OPEN WITH STANDARD INSTRUMENTATION Greater inaccuracy in tibial component alignment and limb alignment Fisher DA et al. (J Arthrop 2003) Hamilton WG et al. (J Arthrop 2006)

20 OUTLIERS IN ALIGNMENT IN UKA WITH CONVENTIONAL METHODS 40-60% of cases are malaligned beyond 2 of plan Keene G et al JBJS Br 2006; Cobb J et al JBJS Br 2006

21 RATIONALE OF ROBOTICS FOR UKA Simplify the procedure Reduce the amount of instrumentation Eliminate surgical steps Enhance accuracy Bone preparation/component alignment Soft tissue balance Improve clinical results Lonner JH. American Journal of Orthopedics 2009

22 SEMI-AUTONOMOUS ROBOTICS IN KNEE ARTHROPLASTY IN U.S. Virtual planning Bone resection Component sizing Implant alignment Soft tissue balancing

23 1 ST GENERATION SYSTEM Image based CT planning and computer guidance Balance & alignment Implant positioning and sizing Intraop virtual gap balancing Bone prep with 6 mm burr attached to robotic arm

24 1 ST GENERATION SEMI-AUTONOMOUS ROBOTIC ARM FOR UKA: Haptic constraint Efficient Accurate Safe Image-based (preop CT scan)

25 DOWNSIDES OF 1 ST GENERATION SEMI-AUTONOMOUS ROBOTIC SYSTEM Capital expense Preop CT scan Additional expense Denials common; high copays; bundled payments Hospitals eat cost Time/Inconvenience Radiation exposure

26 2 ND GENERATION SEMI-AUTONOMOUS ROBOTIC SYSTEMS: Image-free (No CT scan) Intraop registration/mapping/planning Intraop gap balancing Burr Speed/Exposure control Cost favorable 35% being used in ASC s for UKA

27 SURGICAL TECHNIQUES

28 IMAGE FREE SYSTEM: SURFACE MAPPING

29 DYNAMIC INTRAOP GAP BALANCING

30 SELECTION OF IMPLANT SIZE/POSITION AND VIRTUAL GAP BALANCE

31 VIRTUAL TRACKING OF FEMUR ON TIBIA

32 TECHNIQUE: BONE PREPARATION

33 PREPARED SURFACE

34 CT-BASED SYSTEM: PREOP PLANNING

35 IMAGE-BASED SYSTEM: DYNAMIC SOFT-TISSUE GAP BALANCING Remove osteophytes Tension MCL/LCL Capture tissue tension through ROM Adjust prn

36 IMAGE BASED SYSTEM: HAPTIC CONSTRAINT Bone resection volume based upon planned component placement and size

37 IMAGE-BASED SYSTEM: ASSESSING ACCURACY OF IMPLANT POSITION

38 DATA???

39 KEY STUDIES Accuracy of bone preparation Pre-clinical (cadaveric specimens) and clinical studies Comparison of intraoperative plan for limb alignment with postop limb alignment Clinical (navigated measures) Accuracy of tibial component alignment and volumetric bone preservation Radiographic Learning Curve Safety Radiation avoidance by using image-free systems (eliminating preop CT scans) Survivorship and satisfaction

40 TIBIAL ALIGNMENT -- UKA Initial 31 robotic UKA s with Haptic, CT-based robotic system Matched group of preceding 27 conventional UKA Height, weight, ROM, alignment Study parameter: Tibial alignment (Lonner, John, Conditt CORR 2009)

41 TIBIAL ALIGNMENT -- UKA Variance: 2.6x greater with manual techniques (p<0.05) RMS error: 3.4 (manual) vs. 1.8 (robot) Coronal alignment Avg error: Manual: 2.7 +/- 2.1 more varus Robot: 0.2 +/-1.8 (p<0.0001) (Lonner, John, Conditt CORR 2009)

42 ACCURACY OF COMPONENT POSITIONING IN UKA: SEMI-AUTONOMOUS ROBOT VS. CONVENTIONAL Prospective RCT, 120 patients 62 robotic UKA (Robotic) 58 conventional (Conventional) Component alignment and position determined by CT scan Coronal, sagittal and axial positioning Bell SW et al. J Bone Joint Surg. 2016

43 ACCURACY OF COMPONENT POSITIONING IN UKA: SEMI-AUTONOMOUS ROBOT VS. CONVENTIONAL Robotic assistance had: significantly lower component median implantation errors in all 3 component parameters (p<0.01) Significantly fewer outliers >2 of target positions Bell SW et al. J Bone Joint Surg. 2016

44 PRE-CLINICAL ACCURACY 25 cadaveric specimens Image-free semi-autonomous system (2 nd Generation robot) Medial UKA 3 surgeons Lonner, Smith, Picard, Hamlin - Clin Orthop 2014

45 ANALYSIS METHOD Preop plan Postop analysis Optical probe inserted into implant divots Surface positions mapped Postop position compared to plan Lonner, Smith, Picard, Hamlin - Clin Orthop 2014

46 ALIGNMENT: SEMI-AUTONOMOUS ROBOTS VS. MANUAL 2.6x less variability than manual techniques (p<0.05) RMS Error Image-Free CT-Based Manual Flex/Ext ( ) Varus/Valgus ( ) Int/Ext ( ) Prox/Dist (mm) Ant/Post (mm) Med/Lat (mm) Dunbar et al J Arthrop 2012 Jenny J Arthrop 2002 Lonner et al CORR 2014

47 ALIGNMENT: NO APPARENT DIFFERENCE -- CT-BASED VS IMAGE-FREE ROBOTIC SYSTEMS 6 wks post Image- free 6 yrs post CT-based

48 PLANNED VERSUS ACHIEVED LIMB ALIGNMENT 65 cases, image-free robotic system Multiple surgeons Postop limb alignment 1 from plan 92% (60/65) F Picard, A Gregori, J Bellemans, J Lonner, J Smith, D Gonzales, A Simone, B Jaramaz CAOS July 2014

49 TIBIAL RESECTION (ROBOTIC VS. CONVENTIONAL) Industry Data 27,989 conventional UKA s 8421 semi-autonomous robotic UKA s Studied variable: tibial poly thickness Implications for revision to TKA Complexity, need for augments/stems Robotic Conventional 8 mm 10 mm Ponzio DY, Lonner JH. Am J Orthop 2016

50 TIBIAL RESECTION (POLY SIZES) 8-mm and 9-mm polyethylene inserts Robotic group: 93.6% Conventional group: 84.5% (P <.0001). Aggressive tibial resection, requiring tibial inserts 10 mm Robotic group: 6.4% Conventional group: 15.5% Tibial inserts >11 mm Robotic group: 0.3% Conventional group: 5.7% No differences between 2 semi-autonomous robots Ponzio DY, Lonner JH. Am J Orthop 2016

51 LEARNING CURVE Eleven novice users (2 nd generation image-free system) Precision achieved immediately Mean of 8 procedures to reach a steady state surgical time (95% confidence interval 6-11) Avg. steady state surgical time 45 minutes (range minutes) A Gregori, F Picard, J Lonner, R Marquez, J Smith, A Simone, B Jaramaz - CAOS Abstract 2014

52 Surgical Time (mins) LEARNING CURVE Greatest improvement in Cutting Phase : Average improvement from 42 to 24 minutes. Least improvement in Anatomic Registration and Implant Planning : Average improvement from 14 minutes to 6 minutes. The mean steady state surgical time for all surgeons was 45 minutes (SE 4.3, p<0.001) Learning curve Surgical Case Number

53 GAP BALANCING Final ligament balance after implantation accurate within 0.53 mm compared to dynamic plan Plate JF et al Advances in Orthopedics 2013

54 SAFETY: SEMI-AUTONOMOUS ROBOTIC SYSTEMS Initial 1010 cases Single surgeon (JHL) No robot-related soft tissue complications

55 RADIATION FROM PREOP CT SCANS 236 scans st generation image-based system ED of radiation from LE CT scan: 4.8 +/- 3.0 msv 25% had add l CT scans (est cumulative ED of msv) Note: 10 msv increases risk of fatal cancer by 1 in 2000 Ponzio DY, Lonner JH. J Arthroplasty 2015

56 SURVIVORSHIP AND SATISFACTION 909 consecutive semi-autonomous robotic UKA s 6 surgeons FB metal-backed implant Follow up: mean 30 mos [range, mos] Survivorship: 98.8% (96% if non-responders failed) 92% satisfied in patients without revision COPYRIGHT 2016 THE KNEE SOCIETY Pearle AD et al. Knee 2017

57 ROBOTICS FOR TKA? 100 TKA s 50 conventional 50 autonomous robotic-assisted (currently not approved for use in U.S.) Mechanical axis outliers >3 : Robotic: 0% Conventional: 24% No differences in ROM or function scores Song EK, Bargar WL et al. Clin Orthop 2013

58 ROBOTICS FOR TKA? Prospective RCT 60 TKA s 29 conventional 31 autonomous robotic-assisted (currently not approved for use in U.S.) Mechanical axis outliers >3 : Robotic: 0% Conventional: 19% (p=0.05) Joint line outliers (>5mm): Robotic: 3.2% Conventional: 20% (p=0.05) Liow MHL et al. J Arthrop 2014

59 ROBOTICS FOR TKA Image-free semi-autonomous system (FDA approved) 108 initial cases Radiographic alignment data: Mechanical axis within 3 : 91%* Tibial component alignment within 3 : 99% Femoral axis alignment within 3 : 99% COPYRIGHT 2016 THE KNEE SOCIETY * Unpublished data suggests improved mechanical alignment with new kinematic balancing algorithm Koenig JA, Plaskos C. Influence of Pre-Operative Deformity on Surgical Accuracy and Time in Robotic-Assisted TKA. Bone Joint J 2013;95-B (S-28) 62

60 CONCLUSION: ROBOTICS Image-free vs CT based Autonomous vs. semi-autonomous Cost favorable? ASC-feasible? Expanding applications UKA, PFA, BiKA THA, TKA Etc, etc.

61 CONCLUSION: ROBOTICS Semi-autonomous systems: Accurate bone preparation, implant position, soft tissue gap balance Safe Further study needed to determine: Functional outcomes Impact on late results/durability

62 CONCLUSION: ROBOT Medicine is prime for a disruption Growing influence of smart technologies in knee arthroplasty Robotics fits into that paradigm Exponential utilization and development Stay tuned

63 THANK YOU.